hackerearth

MARCH 5, 2019

The Internet of Things (IoT) is a system of interrelated devices that have unique identifiers and can autonomously transfer data over a network. The greatest benefit of IIoT is predictive maintenance i.e. it enables IIoT systems to gather real-time data, analyze it, and derive predictions on when machinery is likely to fail.

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Internet of things Artificial Inteligence Technical Review Data 110

Kainexus

MAY 2, 2024

It encompasses adopting cloud computing, big data analytics, artificial intelligence, Internet of Things (IoT), and other cutting-edge technologies to drive efficiency, innovation, and growth. In this blog post, we'll delve into the intricacies of digital transformation outcomes, focusing on ROI.

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Acuvate

DECEMBER 7, 2022

Industrial IIoT, in particular, in the form of sensors, flow meters, and edge devices, are being used to collect on-field data to create situational awareness and identify leaks, sewer overflows, and faulty equipment before these require costly repairs. How are sustainable technological solutions enabling Smart Water Management (SWM)?

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Data Artificial Inteligence Management Technical Review 78

Leveraging Networks

MARCH 12, 2019

This is done through the incorporation of various intelligent technologies into a business’s overall approach. Examples include artificial intelligence, machine learning, the Internet of Things and blockchain. This can involve anything from vehicles to machines or even home appliances.

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mjvinnovation

APRIL 15, 2019

In the coming weeks, we will post a series of posts here on the blog, where we will explain the details of the transformations guided by the new Data Age – which still faces a lot of different organizations. That’s why data never sleeps. In the midst of this scenario, not having a data strategy can be very dangerous.

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Data Artificial Inteligence Internet of things Analysis 66

Acuvate

JUNE 28, 2019

2 Artificial Intelligence (AI). AI has quickly become a popular application for many business sectors because of its focus on making intelligent machines that are capable of solving some problems as well as (or better than) people can. Learn More: Enterprise AI: The Adoption Strategy & Practical Solutions. #3

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Linda Bernardi

JULY 24, 2017

Mega Data 2. Culture of Agility There has never been a more exciting time for artificial intelligence in enterprises. We are past Big Data (which occurred with the advent of mobile, apps and social media), and are in the Hyper-Data stage. It will require AI and machine learning (ML).

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